专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

61. 发明授权

US07809185B2 Extracting dominant colors from images using classification techniques 有权
标题翻译：使用分类技术从图像中提取主色
公开(公告)号：US07809185B2
公开(公告)日：2010-10-05
申请号：US11533953
申请日：2006-09-21
申请人： Mingjing Li , Wei-Ying Ma , Zhiwei Li , Yuanhao Chen
发明人： Mingjing Li , Wei-Ying Ma , Zhiwei Li , Yuanhao Chen
IPC分类号： G06K9/62
CPC分类号： G06K9/4652 , G06T7/90 , G06T2207/10024 , G06T2207/20081
摘要： A method and system for generating a detector to detect a dominant color of an image is provided. A dominant color system trains a detector to classify colors as being dominant colors of images. The dominant color system trains the detector using a collection of training images. To train the detector, the dominant color system first identifies candidate dominant colors of the training images. The dominant color system then extracts features of the candidate dominant colors. The dominant color system also inputs an indication of dominance of each of the candidate dominant colors. The dominant color system then trains a detector to detect the dominant color of images using the extracted features and indications of dominance of the candidate dominant colors as training data.
摘要翻译：提供了一种用于生成用于检测图像的主要颜色的检测器的方法和系统。主色系统训练检测器将颜色分类为图像的主要颜色。主要颜色系统使用训练图像的集合训练检测器。为了训练检测器，主要颜色系统首先识别训练图像的候选主色。主要颜色系统然后提取候选主色的特征。主要颜色系统还输入每种候选主色的优势指示。主要颜色系统然后训练检测器以使用提取的特征和候选主色优势的指示作为训练数据来检测图像的主要颜色。

62. 发明授权

US07647331B2 Detecting duplicate images using hash code grouping 有权
标题翻译：使用哈希码分组检测重复的图像
公开(公告)号：US07647331B2
公开(公告)日：2010-01-12
申请号：US11277727
申请日：2006-03-28
申请人： Mingjing Li , Bin Wang , Wei-Ying Ma , Zhiwei Li
发明人： Mingjing Li , Bin Wang , Wei-Ying Ma , Zhiwei Li
IPC分类号： G06F7/00 , G06F17/00 , G06K9/56 , G06K9/68
CPC分类号： G06F17/30864
摘要： A duplicate image detection system generates an image table that maps hash codes of images to their corresponding images. The image table may group images according to their group identifiers generated from the most significant elements of the hash codes based on significance of the elements in representing an image. The image table thus segregates images by their group identifiers. To detect a duplicate image of a target image, the detection system generates a target hash code for the target image. The detection system then identifies the group of the target image based on the group identifier of the target hash code. After identifying the group identifier, the detection system searches the corresponding group table to identify hash codes that have values that are similar to the target hash code. The detection system then selects the images associated with those similar hash codes as being duplicates of the target image.
摘要翻译：复制图像检测系统生成将图像的哈希码映射到其对应图像的图像表。图像表可以根据基于代表图像的元素的重要性从哈希码的最重要元素生成的组标识符来对图像进行分组。因此，图像表通过其组标识符隔离图像。为了检测目标图像的重复图像，检测系统生成目标图像的目标散列码。然后，检测系统基于目标散列码的组标识符来识别目标图像的组。在识别组标识符之后，检测系统搜索对应的组表以识别具有与目标散列码相似的值的散列码。然后，检测系统选择与这些类似的哈希码相关联的图像作为目标图像的重复。

63. 发明申请

US20090324077A1 Patch-Based Texture Histogram Coding for Fast Image Similarity Search 有权
标题翻译：基于贴图的纹理直方图编码快速图像相似度搜索
公开(公告)号：US20090324077A1
公开(公告)日：2009-12-31
申请号：US12147832
申请日：2008-06-27
申请人： Lei Wu , Mingjing Li
发明人： Lei Wu , Mingjing Li
IPC分类号： G06K9/00 , G06K9/34 , G06K9/64
CPC分类号： H04N21/835 , G06F17/30247 , G06K9/4642 , G06T7/44 , G06T7/97 , G06T2207/10008 , G06T2207/20021 , H04N21/44008 , H04N21/44236
摘要： Techniques for identifying copied images based on an original image are described. The identifying copied image is based on creating unique and identifiable features that in turn are used to generate multiple histograms. The histograms are generated by patches of the image, where the patches are created by equally dividing the image. The combined patch histograms are representative of the image.
摘要翻译：描述了基于原始图像识别复制图像的技术。识别复制的图像基于创建唯一且可识别的特征，其又被用于生成多个直方图。直方图由图像的补丁生成，其中通过均匀分割图像来创建补丁。组合的斑块直方图代表图像。

64. 发明申请

US20090076800A1 Dual Cross-Media Relevance Model for Image Annotation 有权
标题翻译：图像注释的双重跨媒体相关性模型
公开(公告)号：US20090076800A1
公开(公告)日：2009-03-19
申请号：US11956331
申请日：2007-12-13
申请人： Mingjing Li , Jing Liu , Bin Wang , Zhiwei Li , Wei-Ying Ma
发明人： Mingjing Li , Jing Liu , Bin Wang , Zhiwei Li , Wei-Ying Ma
IPC分类号： G06F17/21
CPC分类号： G06F17/241 , G06F17/2735
摘要： A dual cross-media relevance model (DCMRM) is used for automatic image annotation. In contrast to the traditional relevance models which calculate the joint probability of words and images over a training image database, the DCMRM model estimates the joint probability by calculating the expectation over words in a predefined lexicon. The DCMRM model may be advantageous because a predefined lexicon potentially has better behavior than a training image database. The DCMRM model also takes advantage of content-based techniques and image search techniques to define the word-to-image and word-to-word relations involved in image annotation. Both relations can be estimated by using image search techniques on the web data as well as available training data.
摘要翻译：双重跨媒体相关性模型（DCMRM）用于自动图像注释。与在训练图像数据库中计算单词和图像的联合概率的传统相关性模型相反，DCMRM模型通过计算预定义词典中的单词的期望来估计联合概率。 DCMRM模型可能是有利的，因为预定义词典潜在地具有比训练图像数据库更好的行为。 DCMRM模型还利用基于内容的技术和图像搜索技术来定义图像注释中涉及的单词到图像和单词对字的关系。可以通过使用图像搜索技术对网络数据以及可用的训练数据来估计这两个关系。

65. 发明申请

US20090063455A1 Bipartite Graph Reinforcement Modeling to Annotate Web Images 有权
标题翻译：用于注释Web图像的二分图加固建模
公开(公告)号：US20090063455A1
公开(公告)日：2009-03-05
申请号：US11848157
申请日：2007-08-30
申请人： Mingjing Li , Wei-Ying Ma , Zhiwei Li , Xiaoguang Rui
发明人： Mingjing Li , Wei-Ying Ma , Zhiwei Li , Xiaoguang Rui
IPC分类号： G06F17/30
CPC分类号： G06F17/30265 , G06F17/30864
摘要： Systems and methods for bipartite graph reinforcement modeling to annotate web images are described. In one aspect the systems and methods implement bipartite graph reinforcement modeling operations to identify a set of annotations that are relevant to a Web image. The systems and methods annotate the Web image with the identified annotations. The systems and methods then index the annotated Web image. Responsive to receiving an image search query from a user, wherein the image search query comprises information relevant to at least a subset of the identified annotations, the image search engine service presents the annotated Web image to the user.
摘要翻译：描述了用于注释网络图像的二分图加强建模的系统和方法。在一个方面，系统和方法实现二分图加强建模操作，以识别与Web图像相关的一组注释。系统和方法用已识别的注释注释Web图像。系统和方法然后索引注释的Web图像。响应于从用户接收图像搜索查询，其中所述图像搜索查询包括与所识别的注释的至少一个子集相关的信息，所述图像搜索引擎服务将所述注释的Web图像呈现给所述用户。

66. 发明申请

US20070239756A1 Detecting Duplicate Images Using Hash Code Grouping 有权
标题翻译：使用哈希代码分组检测重复的图像
公开(公告)号：US20070239756A1
公开(公告)日：2007-10-11
申请号：US11277727
申请日：2006-03-28
申请人： Mingjing Li , Bin Wang , Wei-Ying Ma , Zhiwei Li
发明人： Mingjing Li , Bin Wang , Wei-Ying Ma , Zhiwei Li
IPC分类号： G06F7/00
CPC分类号： G06F17/30864
摘要： A duplicate image detection system generates an image table that maps hash codes of images to their corresponding images. The image table may group images according to their group identifiers generated from the most significant elements of the hash codes based on significance of the elements in representing an image. The image table thus segregates images by their group identifiers. To detect a duplicate image of a target image, the detection system generates a target hash code for the target image. The detection system then identifies the group of the target image based on the group identifier of the target hash code. After identifying the group identifier, the detection system searches the corresponding group table to identify hash codes that have values that are similar to the target hash code. The detection system then selects the images associated with those similar hash codes as being duplicates of the target image.
摘要翻译：复制图像检测系统生成将图像的哈希码映射到其对应图像的图像表。图像表可以根据基于代表图像的元素的重要性从哈希码的最重要元素生成的组标识符来对图像进行分组。因此，图像表通过其组标识符隔离图像。为了检测目标图像的重复图像，检测系统生成目标图像的目标散列码。然后，检测系统基于目标散列码的组标识符来识别目标图像的组。在识别组标识符之后，检测系统搜索对应的组表以识别具有与目标散列码相似的值的散列码。然后，检测系统选择与这些类似的哈希码相关联的图像作为目标图像的重复。

67. 发明授权

US07277732B2 Language input system for mobile devices 有权
标题翻译：移动设备语言输入系统
公开(公告)号：US07277732B2
公开(公告)日：2007-10-02
申请号：US09843358
申请日：2001-04-24
申请人： Zheng Chen , Mingjing Li , Feng Zhang , Rui Yang , Jianfeng Gao
发明人： Zheng Chen , Mingjing Li , Feng Zhang , Rui Yang , Jianfeng Gao
IPC分类号： A04B1/38
CPC分类号： G06F3/0236 , G06F3/018 , G06F3/0237 , H04M1/72519 , H04M2250/58 , H04M2250/70
摘要： A language system facilitates entry of an input string into a mobile device using discrete keys on a keypad, such as a 10-key keypad. The numeric keys have associated letters of an alphabet. The key input is representative of one or more Chinese phonetic characters. Based on this input string, the language system derives the most likely Chinese corresponding language characters intended by the user. The language system uses multiple different search engines and language models to aid in deriving the most probable Chinese language characters. When the language system recognizes possible Chinese language characters, the mobile device displays the possible Chinese language characters for user selection of the possible Chinese language characters and/or further input of one or more Chinese phonetic characters. In this manner, the language system adopts a modeless entry methodology that eliminates conventional mode switching between input and selection operations.
摘要翻译：语言系统有助于使用键盘上的离散键（诸如10键键盘）将输入串输入到移动设备中。数字键具有字母的相关字母。关键输入是一个或多个汉语拼音字符的代表。基于该输入字符串，语言系统导出用户想要的最可能的中文对应语言字符。语言系统使用多种不同的搜索引擎和语言模型来帮助推导出最可能的中文字符。当语言系统识别可能的中文字符时，移动设备显示可能的汉语字符，用于选择可能的中文字符和/或进一步输入一个或多个汉语拼音字符。以这种方式，语言系统采用无模式输入方法，消除了输入和选择操作之间的常规模式切换。

68. 发明授权

US07043422B2 Method and apparatus for distribution-based language model adaptation 失效
公开(公告)号：US07043422B2
公开(公告)日：2006-05-09
申请号：US09945930
申请日：2001-09-04
申请人： Jianfeng Gao , Mingjing Li
发明人： Jianfeng Gao , Mingjing Li
IPC分类号： G06F17/27
CPC分类号： G06F17/2715 , G10L15/065 , G10L15/1815
摘要： A method and apparatus are provided for adapting a language model to a task-specific domain. Under the method and apparatus, the relative frequency of n-grams in a small training set (i.e. task-specific training data set) and the relative frequency of n-grams in a large training set (i.e. out-of-domain training data set) are used to weight a distribution count of n-grams in the large training set. The weighted distributions are then used to form a modified language model by identifying probabilities for n-grams from the weighted distributions.

69. 发明申请

US20110264659A1 TRAINING A RANKING FUNCTION USING PROPAGATED DOCUMENT RELEVANCE 审中-公开
标题翻译：使用传播文件相关性来训练排序功能
公开(公告)号：US20110264659A1
公开(公告)日：2011-10-27
申请号：US13175804
申请日：2011-07-01
申请人： Jue Wang , Mingjing Li , Wei-Ying Ma , Zhiwei Li
发明人： Jue Wang , Mingjing Li , Wei-Ying Ma , Zhiwei Li
IPC分类号： G06F17/30
CPC分类号： G06F16/951 , G06F16/3331
摘要： A method and system for propagating the relevance of labeled documents to a query to unlabeled documents is provided. The propagation system provides training data that includes queries, documents labeled with their relevance to the queries, and unlabeled documents. The propagation system then calculates the similarity between pairs of documents in the training data. The propagation system then propagates the relevance of the labeled documents to similar, but unlabeled, documents. The propagation system may iteratively propagate labels of the documents until the labels converge on a solution. The training data with the propagated relevances can then be used to train a ranking function.
摘要翻译：提供了一种用于将标记的文档的相关性传播到未标记文档的查询的方法和系统。传播系统提供包括查询，标记为与查询相关的文档以及未标记的文档的培训数据。传播系统然后计算训练数据中文档对之间的相似度。传播系统然后将标记的文档的相关性传播到类似但未标记的文档。传播系统可以迭代地传播文档的标签，直到标签收敛在解决方案上。然后可以使用具有传播相关性的训练数据来训练排序功能。

70. 发明申请

US20090060351A1 Visual Language Modeling for Image Classification 有权
标题翻译：图像分类的视觉语言建模
公开(公告)号：US20090060351A1
公开(公告)日：2009-03-05
申请号：US11847959
申请日：2007-08-30
申请人： Mingjing Li , Wei-Ying Ma , Zhiwei Li , Lei Wu
发明人： Mingjing Li , Wei-Ying Ma , Zhiwei Li , Lei Wu
IPC分类号： G06K9/62
CPC分类号： G06K9/4685 , G06K9/4642 , G06K9/6278
摘要： Systems and methods for visual language modeling for image classification are described. In one aspect the systems and methods model training images corresponding to multiple image categories as matrices of visual words. Visual language models are generated from the matrices. In view of a given image, for example, provided by a user or from the Web, the systems and methods determine an image category corresponding to the given image. This image categorization is accomplished by maximizing the posterior probability of visual words associated with the given image over the visual language models. The image category, or a result corresponding to the image category, is presented to the user.
摘要翻译：描述了用于图像分类的视觉语言建模的系统和方法。在一个方面，系统和方法将对应于多个图像类别的训练图像建模为视觉词的矩阵。视觉语言模型是从矩阵生成的。考虑到例如由用户或从Web提供的给定图像，系统和方法确定对应于给定图像的图像类别。这种图像分类是通过在视觉语言模型上最大化与给定图像相关联的视觉词的后验概率来实现的。图像类别或与图像类别对应的结果被呈现给用户。

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式